INTELLIGENT WEB

International Teaching INTELLIGENT WEB

0522500137
COMPUTER SCIENCE
EQF7
COMPUTER SCIENCE
2021/2022



YEAR OF DIDACTIC SYSTEM 2016
SECONDO SEMESTRE
CFUHOURSACTIVITY
648LESSONS
Objectives
TEACHING GOALS
THE GOAL OF THE COURSE IS TO PROVIDE STUDENTS WITH THE FOUNDATIONS OF THE WEB OF DATA PARADIGM FOR STUDYING AND DESCRIBING DOMAINS OF INTEREST THROUGH KNOWLEDGE BASES, LINKED DATA AND INFERENCE TOOLS.

KNOWLEDGE AND UNDERSTANDING
STUDENTS WILL GAIN KNOWLEDGE FOR CONCEPTUAL AND LOGICAL MODELING OF A DOMAIN OF INTEREST BY USING SCHEMAS BASED ON RDF, RDF-S AND OWL WITH THE CORRESPONDING SYNTAX FOR SERIALIZATION. THEY WILL ALSO ACQUIRE METHODS AND TECHNIQUES TO EXTRACT DATA FROM SEMANTIC KNOWLEDGE BASES THROUGH THE SPARQL LANGUAGE / PROTOCOL.

APPLYING KNOWLEDGE AND UNDERSTANDING
STUDENTS WILL BE ABLE TO:
•USE ONTOLOGICAL LANGUAGES AND TOOLS TO DEFINE AND CONSTRUCT KNOWLEDGE BASES FOLLOWING THE GENERAL APPROACH OF WEB OF DATA,
•MODEL AND INTEGRATE SEMANTIC ASPECTS OF WEB ORIENTED APPLICATIONS,
•USE W3C FACILITIES,
•APPLY INFERENCE TOOLS,
•USE OPEN SOURCE SOFTWARE TO REALIZE KNOWLEDGE BASES.
Prerequisites
NO PREREQUISITE.
Contents
THE COURSE INTRODUCES THE MAIN CONCEPTS RELATED TO SEMANTIC WEB AND AIMS TO MAKE THE STUDENT ACQUIRE KNOWLEDGE ABOUT MAIN TOPICS OF THE SEMANTIC WEB, THE KNOWLEDGE REPRESENTATION METHODOLOGIES (ONTOLOGIES) AND SEMANTIC MARKUP LANGUAGES, RANGING FROM XML, TO RDF(S), AND OWL. CONCEPTS OF “WEB OF DATA AND LINKED DATA” WILL BE ALSO DISCUSSED.
Teaching Methods
TEACHING INCLUDES 48 HOURS OF LECTURES AND EXERCISES (6 CFUS). IN PARTICULAR, 32 HOURS OF LECTURES (4 CFUS) AND 16 HOURS OF GUIDED LABORATORY EXERCISES (2 CFUS) ARE PROVIDED.
LECTURES AND EXERCISES ARE COMPLEMENTED BY WEB/SEM -INARS CONDUCTED BY EXPERTS AND PROFESSIONALS IN THE WEB OF DATA FIELD INVITED TO RELATE ON TOPICS OF PARTICULAR INTEREST AND TO PRESENT INNOVATIVE TECHNOLOGY SOLUTIONS. LABORATORY ACTIVITIES ARE ALSO USED FOR ANALYSIS OF CASE STUDIES AND FOR THE REALIZATION OF A PROJECT. THE USE OF AN OPEN SOURCE SOFTWARE ALLOWS STUDENTS TO WORK BEYOND THE TIME OF ACCESS TO THE LABORATORY FOR INDIVIDUAL TUTORIALS.
Verification of learning
THE ACHIEVEMENT OF THE OBJECTIVES OF THE COURSE IS CERTIFIED BY PASSING AN EVALUATION EXAM. THE EXAM CONSISTS IN THE DEFENCE OF A GIVEN PROFESSIONAL PROJECT IMPLEMENTED BY A TEAM OF STUDENTS, AND AN ORAL EXAM. THE IMPLEMENTATION OF THE PROJECT IS PRELIMINARY TO THE ORAL TEST AND ITS GOAL IS TO IMPLEMENT AN APPLICATION THAT USES LINKED (OPEN) DATA. ORAL EXAMINATION IS MEANT TO EVALUATE THE PROJECT AND TO ASSESS THE GAINED KNOWLEDGE. THE EVALUATION CRITERIA INCLUDE THE COMPLETENESS AND THE CORRECTNESS OF THE REALIZED ARTEFACTS, TOGETHER WITH THE FLUENCY AND THE CLARITY OF PRESENTATION OF THE COURSE CONTENTS.
THE RESULT OF THE ORAL EXAM AND THE PROJECT DISCUSSION CONTRIBUTE TO THE FORMULATION OF FINAL VOTE WITH WEIGHT OF APPROXIMATELY 40% AND 60% RESPECTIVELY.
Texts
-DI NOIA, DE VIRGILIO, DI SCIASCIO, DONINI, SEMANTIC WEB: TRA ONTOLOGIE E OPEN DATA. APOGEO
-ANTONIOU G. AND VAN HARMELEN F., SEMANTIC WEB PRIMER, THE MIT PRESS, 2008

RECOMMENDED BOOKS
-PASCAL HITZLER, MARKUS KRÖTZSCH, SEBASTIAN RUDOLPH, FOUNDATIONS OF SEMANTIC WEB TECHNOLOGIES
CHAPMAN & HALL/CRC, 2009
More Information
FURTHER INFORMATION CAN BE REQUIRED AT TEACHER'S EMAIL AND FOUND AT E-LEARNING PLATFORM FROM THE DIPARTIMENTO DI INFORMATICA
HTTP://ELEARNING.INFORMATICA.UNISA.IT/EL-PLATFORM/
  BETA VERSION Data source ESSE3